The Impact of Perceived Sleep, Mood and Alcohol Use on Verbal, Physical and Sexual Assault Experiences among Student Athletes and Student Non-Athletes

Previous research has shown that student athletes are more likely to be involved in a physical altercation or be a victim of verbal, physical and/or sexual abuse than student non-athletes, which can have long-lasting negative effects on mood, behavior and quality of life. In addition, among college students, sleep difficulties are ubiquitous and may deteriorate the unique life experience that university represents. The influences of poor sleep quality, mood and alcohol consumption related to these events are examined here between student athletes and student non-athletes. A series of hierarchical logistic regressions explored the relationship between verbal, physical and sexual assault risk factors. Results suggest that poor sleep, alcohol consumption and mood are all associated with exposure to a physical altercation or episode of abuse, irrespective of athlete status. Results also show that variables targeting self-reported difficulty sleeping and experiences of verbal, physical and sexual assault were positively associated. However, given the cross-sectional nature of the study, it is impossible to establish the direction of these relationships

Sleep Health, Individual Characteristics, Lifestyle Factors, and Marathon Completion Time in Marathon Runners: A Retrospective Investigation of the 2016 London Marathon

Despite sleep health being critically important for athlete performance and well-being, sleep health in marathoners is understudied. This foundational study explored relations between sleep health, individual characteristics, lifestyle factors, and marathon completion time. Data were obtained from the 2016 London Marathon participants. Participants completed the Athlete Sleep Screening Questionnaire (ASSQ) along with a brief survey capturing individual characteristics and lifestyle factors. Sleep health focused on the ASSQ sleep difficulty score (SDS) and its components. Linear regression computed relations among sleep, individual, lifestyle, and marathon variables. The analytic sample (N = 943) was mostly male (64.5%) and young adults (66.5%). A total of 23.5% of the sample reported sleep difficulties (SDS ≥ 8) at a severity warranting follow-up with a trained sleep provider. Middle-aged adults generally reported significantly worse sleep health characteristics, relative to young adults, except young adults reported significantly longer sleep onset latency (SOL). Sleep tracker users reported worse sleep satisfaction. Pre-bedtime electronic device use was associated with longer SOL and longer marathon completion time, while increasing SOL was also associated with longer marathon completion. Our results suggest a deleterious influence of pre-bedtime electronic device use and sleep tracker use on sleep health in marathoners. Orthosomnia may be a relevant factor in the relationship between sleep tracking and sleep health for marathoners

Disassembling insomnia symptoms and their associations with depressive symptoms in a community sample: the differential role of sleep symptoms, daytime symptoms, and perception symptoms of insomnia

Objective: Insomnia and depression are closely related. However, few studies have investigated whether certain insomnia symptoms differentially relate to certain depressive symptoms. The present study aimed to examine relationship between specific types of insomnia symptoms (sleep symptoms, daytime symptoms, and perception symptoms) and specific symptoms of depression. Design: Cross-sectional, observational study data from the Sleep, Health, Activity, Diet and Environment and Social Factors (SHADES) Survey. Setting: Community-level population. Participants: A total of 1003 community-based adults aged 22–60 from the Philadelphia area. Measurements: Insomnia symptoms were represented by scores of sleep symptoms, daytime symptoms and perception symptoms, derived from the Insomnia Severity Index (ISI). Depression symptoms were assessed with the items of the Patient Health Questionnaire 9 (PHQ-9). Results: A Confirmatory Factor Analysis (CFA) supported the three-factor model based on ISI data. Binary logistic regressions examined independent associations between the three insomnia symptom types and individual depression symptoms. Sleep symptoms were more strongly associated with physiological aspects of depressive symptoms (appetite symptoms, psychomotor symptoms, and suicidal ideation). The daytime symptoms, on the other hand, were significantly associated with almost all depressive symptoms, except for appetite. Moreover, daytime symptoms were exclusively related to cognitive symptoms of depression (eg, trouble concentrating). The perception symptoms were independently associated with mood symptoms, tiredness, appetite, and judgment of oneself as a failure, but not with psychomotor, cognitive and suicidal ideation symptoms. Conclusion: Daytime symptoms and perception symptoms of insomnia were more strongly associated with a full range of depressive symptoms than sleep symptoms. The sleep symptoms were mainly associated with more physiological symptoms of depression, implicating more biological mechanisms. Further research is needed regarding how these types of insomnia symptoms differentially related to multiple health consequences

Sleep Health, Individual Characteristics, Lifestyle Factors, and Marathon Completion Time in Marathon Runners: A Retrospective Investigation of the 2016 London Marathon

Despite sleep health being critically important for athlete performance and well-being, sleep health in marathoners is understudied. This foundational study explored relations between sleep health, individual characteristics, lifestyle factors, and marathon completion time. Data were obtained from the 2016 London Marathon participants. Participants completed the Athlete Sleep Screening Questionnaire (ASSQ) along with a brief survey capturing individual characteristics and lifestyle factors. Sleep health focused on the ASSQ sleep difficulty score (SDS) and its components. Linear regression computed relations among sleep, individual, lifestyle, and marathon variables. The analytic sample (N = 943) was mostly male (64.5%) and young adults (66.5%). A total of 23.5% of the sample reported sleep difficulties (SDS ≥ 8) at a severity warranting follow-up with a trained sleep provider. Middle-aged adults generally reported significantly worse sleep health characteristics, relative to young adults, except young adults reported significantly longer sleep onset latency (SOL). Sleep tracker users reported worse sleep satisfaction. Pre-bedtime electronic device use was associated with longer SOL and longer marathon completion time, while increasing SOL was also associated with longer marathon completion. Our results suggest a deleterious influence of pre-bedtime electronic device use and sleep tracker use on sleep health in marathoners. Orthosomnia may be a relevant factor in the relationship between sleep tracking and sleep health for marathoners

The key role of insomnia and sleep loss in the dysregulation of multiple systems involved in mood disorders: A proposed model

Mood disorders are amongst the most prevalent and severe disorders worldwide, with a tendency to be recurrent and disabling. Although multiple mechanisms have been hypothesized to be involved in their pathogenesis, just a few integrative theoretical frameworks have been proposed and have yet to integrate comprehensively all available findings. As such, a comprehensive framework would be quite useful from a clinical and therapeutic point of view in order to identify elements to evaluate and target in the clinical practice. Because conditions of sleep loss, which include reduced sleep duration and insomnia, are constant alterations in mood disorders, the aim of this paper was to review the literature on their potential role in the pathogenesis of mood disorders and to propose a novel theoretical model. According to this hypothesis, sleep should be considered the main regulator of several systems and processes whose dysregulation is involved in the pathogenesis of mood disorders. The model may help explain why sleep disturbances are so strikingly linked to mood disorders, and underscores the need to evaluate, assess and target sleep disturbances in clinical practice, as a priority, in order to prevent and treat mood disorders